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, Radioecology, Mineralogy, Geology or related field Experience in experimental and analytical work and in the evaluation of extensive analytical data sets Knowledge of handling radioactive substances is desirable
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) and should be used for a doctorate. Participation in the accompanying doctoral program is compulsory. This serves to impart both scientific and methodological knowledge and offers the opportunity
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Completed university studies (Master/Diploma) in the field of Chemistry, Radiochemistry, Radiopharmacy, Radioecology or related field Excellent knowledge of a broad range of organic chemistry and analytical
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atomistic simulations, high-performance computing, and the application of AI-based methods Basic knowledge in photovoltaics and solid-state materials for energy application Ability to work individually and in
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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degree of independence and commitment Very reliable and conscientious style of working Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be
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a doctorate. We are looking for: candidates with a Master’s degree in mathematics or a closely related field and with a strong background in probability theory. Prior knowledge in spatial stochastic
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for diversity Desirable knowledge and skills include: o Understanding of the principles that define DNA, RNA, protein structures, functions, dynamics and interactions o Experience in plant work
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necessary knowledge and a broad range of skills for the successful completion of the project. Basic knowledge of data analysis or programming and good English skills are desirable. We value independent
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the field of Biotechnology/Biology/Bioprocess engineering or related field Knowledge of genetic engineering, protein production and cell-free approach as well as bioprocess engineering, bioproduction